Heterogeneity and the interpretation of treatment effect estimates from risk adjustment and instrumental variable methods
Heterogeneity and the interpretation of treatment effect estimates from risk adjustment and instrumental variable methods
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DOI：
10.1097/mlr.0b013e318070c069
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发表时间：
2007-10-01
期刊：
影响因子：
3
通讯作者：
Chrischilles, Elizabeth A.
中科院分区：
文献类型：
--
作者：
Brooks, John M.;Chrischilles, Elizabeth A.
目的：比较风险调整方法和工具变量(IV)估计方法在不同患者间治疗效果不同的情况下，使用观察数据对治疗效果估计的解释。我们通过检验相对于乳腺癌切除的保乳手术加放疗(BCSI)对早期乳腺癌(ESBC)生存率的影响来论证这些对比。方法：我们通过使用两种不同的工具(患者住所到最近的放射中心的距离和当地的BCSI率)和控制癌症的分期、分级和位置、年龄、合并症、医院准入、Payer、诊断年份和地区贫困水平来估计1989-1994年爱荷华州癌症登记中心的6185名ESBC患者的离散时间生存模型。然后，我们使用具有稳健标准误差的线性概率方法来估计可比风险调整生存模型。结果：风险调整模型得出的平均生存估计与试验结果相似。有了良好的BCSI选择，这些估计代表了接受BCSI治疗的患者的真实效果的上限。IV估计显示，手术选择受器械影响的患者存在BCSI生存风险，这些估计因器械规格而异。结论：当治疗益处在患者之间不同时，来自观察数据的治疗效果估计仍然对政策制定者有用，但必须正确解释。风险调整方法产生的估计可以评估接受治疗的患者是否从治疗中受益，但必须考虑偏差的方向。相比之下，IV估计可以评估治疗率变化的影响，但在做出这样的推断时，必须考虑选择受仪器影响的患者的特征。
Objectives: To contrast the interpretations of treatment effect estimates using risk adjustment and instrumental variable (IV) estimation methods using observational data when the effects of treatment are heterogeneous across patients. We demonstrate these contrasts by examining the effect of breast conserving surgery plus irradiation (BCSI) relative to mastectomy on early stage breast cancer (ESBC) survival.Methods: We estimated discrete time survival models for 6185 ESBC patients in the 1989-1994 Iowa Cancer Registry via IV estimation using 2 distinct instruments (distance of the patient's residence from the nearest radiation center, and local area BCSI rate) and controlling for cancer stage, grade, and location; age; comorbidity; hospital access; payer; diagnosis year; and area poverty level. We then estimated comparable risk adjustment survival models using linear probability methods with robust standard errors.Results: Risk adjustment models yielded average survival estimates similar to trial results. With favorable BCSI selection, these estimates represent an upper bound of the true effect for patients receiving BCSI. IV estimates showed a BCSI survival risk for patients whose surgery choices were affected by the instruments and these estimates varied with the instrument specification.Conclusions: When treatment benefits are heterogeneous across patients, treatment effect estimates from observational data can still be useful to policymakers, but they must be interpreted correctly. Risk adjustment methods yield estimates that can assess whether the patients who received treatment benefited from the treatment, but the direction of bias must be considered. In contrast, IV estimates can assess the effect of treatment rate changes, but characteristics of patients whose choices were affected by the instruments must be considered when making such inferences.